A recent study by researchers from the University of Bath and collaborating institutions reveals that widespread use of generative AI tools like ChatGPT in the workplace may undermine managers’ ability to develop and apply practical wisdom. The research highlights concerns that excessive dependence on AI-generated solutions could erode critical judgment skills essential for effective leadership.
What Happened
The study, published in the 2026 issue of the Academy of Management Review, analyzed how generative AI influences what is known as “managerial phronesis” — practical wisdom accumulated through real-world experience, reflection, and social interaction. Researchers including Professor Dirk Lindebaum of the University of Bath’s School of Management examined the consequences of managers outsourcing decision-making and problem-solving tasks to AI, especially under time pressure. Their findings indicate a process they term “epistemic deskilling,” where reliance on AI can gradually weaken managers’ knowledge-based capabilities.
Key Facts
The research team, comprising experts from the University of Bath, Ohio State University, the University of Lausanne, and Cardiff University, identified that generative AI’s inability to experience context or emotional nuance leads to responses based solely on existing data patterns rather than moral or situational insight.
Professor Lindebaum explained that managers who use AI as a shortcut may stop engaging in critical questioning, fail to seek diverse perspectives, and lose opportunities to learn from direct human interactions. Conversely, the study also introduces “epistemic upskilling,” where AI can aid managers’ reflection if used to challenge assumptions and test alternative scenarios rather than replace judgment.
The positive potential of AI depends on managerial accountability, as organizations where decisions require justification encourage managers to interrogate AI outputs and actively fill explanatory gaps themselves.
What This Means
This research underscores a key tension in modern workplaces integrating AI tools. While generative AI accelerates task completion and idea generation, it lacks the human capacity for moral discernment and contextual judgment developed through experience. For everyday managers, this means that uncritical reliance on AI outputs risks diminishing essential leadership skills, posing a challenge for organizational decision quality and adaptability over time.
On the other hand, if managers adopt AI as a complementary tool that fuels deeper reflection rather than substitutes their thinking, it can enhance decision-making by encouraging critical engagement and broadening the exploration of alternatives. The study suggests organizations must therefore design workflows and accountability mechanisms that preserve human judgment and learning rather than automate it away. This approach could ultimately influence training practices, performance metrics, and the role of AI governance in managerial contexts.
Background
Prior research has noted the efficiencies generative AI tools bring to routine work tasks, but concerns about “epistemic deskilling” have emerged as a caution against overdependence. Managerial phronesis traditionally arises from continuous exposure to complex human dynamics and the need to balance multiple social, ethical, and organizational factors — areas where AI currently falls short.
What Remains Unclear
The study does not yet clarify how scalable the epistemic deskilling effect is across different industries and management levels, nor how organizational culture factors might mitigate or exacerbate this risk. The long-term impact of sustained AI use on experiential learning processes and managers’ ability to anticipate future challenges requires further empirical investigation.
What Comes Next
The authors, including Professor Lindebaum and colleagues from Ohio State University, Cardiff University, and the University of Lausanne, call for future research to explore specific frameworks that support epistemic upskilling. Continued monitoring of AI’s integration in management roles and assessment of its effects on decision accountability will be essential steps.
Sources
This article is based on reporting and publicly available information from the following sources:
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